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Mikael Valot commented on SPARK-22474: -------------------------------------- I can read the file if I comment out line 581 in org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter {code:java} def checkConversionRequirement(f: => Boolean, message: String): Unit = { if (!f) { // throw new AnalysisException(message) } } {code} > cannot read a parquet file containing a Seq[Map[MyCaseClass, String]] > --------------------------------------------------------------------- > > Key: SPARK-22474 > URL: https://issues.apache.org/jira/browse/SPARK-22474 > Project: Spark > Issue Type: Bug > Components: Spark Core > Affects Versions: 2.1.2, 2.2.0 > Reporter: Mikael Valot > > The following code run in spark-shell throws an exception. It is working fine > in Spark 2.0.2 > {code:java} > case class MyId(v: String) > case class MyClass(infos: Seq[Map[MyId, String]]) > val seq = Seq(MyClass(Seq(Map(MyId("1234") -> "blah")))) > seq.toDS().write.parquet("/tmp/myclass") > spark.read.parquet("/tmp/myclass").as[MyClass].collect() > Caused by: org.apache.spark.sql.AnalysisException: Map key type is expected > to be a primitive type, but found: required group key { > optional binary v (UTF8); > }; > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$.checkConversionRequirement(ParquetSchemaConverter.scala:581) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convertGroupField$2.apply(ParquetSchemaConverter.scala:246) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convertGroupField$2.apply(ParquetSchemaConverter.scala:201) > at scala.Option.fold(Option.scala:158) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertGroupField(ParquetSchemaConverter.scala:201) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:109) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$2.apply(ParquetSchemaConverter.scala:87) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$2.apply(ParquetSchemaConverter.scala:84) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at scala.collection.Iterator$class.foreach(Iterator.scala:893) > at scala.collection.AbstractIterator.foreach(Iterator.scala:1336) > at scala.collection.IterableLike$class.foreach(IterableLike.scala:72) > at scala.collection.AbstractIterable.foreach(Iterable.scala:54) > at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) > at scala.collection.AbstractTraversable.map(Traversable.scala:104) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.org$apache$spark$sql$execution$datasources$parquet$ParquetSchemaConverter$$convert(ParquetSchemaConverter.scala:84) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convertGroupField$1.apply(ParquetSchemaConverter.scala:201) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convertGroupField$1.apply(ParquetSchemaConverter.scala:201) > at scala.Option.fold(Option.scala:158) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertGroupField(ParquetSchemaConverter.scala:201) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:109) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter$ParquetArrayConverter.<init>(ParquetRowConverter.scala:483) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter.org$apache$spark$sql$execution$datasources$parquet$ParquetRowConverter$$newConverter(ParquetRowConverter.scala:298) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter$$anonfun$6.apply(ParquetRowConverter.scala:183) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter$$anonfun$6.apply(ParquetRowConverter.scala:180) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) > at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) > at scala.collection.AbstractTraversable.map(Traversable.scala:104) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter.<init>(ParquetRowConverter.scala:180) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetRecordMaterializer.<init>(ParquetRecordMaterializer.scala:38) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetReadSupport.prepareForRead(ParquetReadSupport.scala:95) > at > org.apache.parquet.hadoop.InternalParquetRecordReader.initialize(InternalParquetRecordReader.java:175) > at > org.apache.parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:190) > at > org.apache.parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:147) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReaderWithPartitionValues$1.apply(ParquetFileFormat.scala:381) > at > org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReaderWithPartitionValues$1.apply(ParquetFileFormat.scala:337) > at > org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:124) > at > org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:174) > at > org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:105) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:234) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:228) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) > at org.apache.spark.scheduler.Task.run(Task.scala:108) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > at java.lang.Thread.run(Thread.java:748) > {code} -- This message was sent by Atlassian JIRA (v6.4.14#64029) 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